list_ss_PARAMETER: list[str] = [] list_ss_POINTS: list[str] = [] list_ss_DATA: list[str] = [] # x : プロセス数 # y : 問題サイズ # z : イテレーション数 list_ss_PARAMETER.append("PARAMETER x") list_ss_PARAMETER.append("PARAMETER y") list_ss_PARAMETER.append("PARAMETER z") list_ss_POINTS.append("POINTS") list_ss_DATA.append("REGION reg") list_ss_DATA.append("METRIC time") for index, row in execTimeAtLulesh.dropna().iterrows(): # print(f"index={index}, row=\n{row}") list_ss_POINTS.append(f"( {row['プロセス数']} {row['問題サイズ']} {row['イテレーション数']} )") list_ss_DATA.append(f"DATA {row['実行時間(s)']} {row['実行時間(s)']} {row['実行時間(s)']}") str_ss_PARAMETER: str = "\n".join(list_ss_PARAMETER) str_ss_PONITS: str = " ".join(list_ss_POINTS) str_ss_DATA: str = "\n".join(list_ss_DATA) filePathInputExtraP = "./extra-p_docker/share/input.txt" with open(filePathInputExtraP, mode="w") as f: f.write(str_ss_PARAMETER) f.write("\n\n") f.write(str_ss_PONITS) f.write("\n\n") f.write(str_ss_DATA)
fig = px.scatter_3d(df_Wait, x="process", y="niter", z="#Call", width=800, height=800) fig.show()df_Waittest_Model_sqrtProcessTimesOtherExpElem_ForMultipleRegression()input_rawDF_cg.columns.tolist()target_rawDF_cg.sort_values("#Call", ascending=False)print( target_rawDF_cg.sort_values("#Call", ascending=False)[:6] .loc[:, ["functionName", "#Call"]] .style.to_latex( caption="ベンチマークプログラムCGで関数コール回数の多い関数(プロセス数256, 初期変数na=15000, 初期変数nonzer=21, 初期変数niter=100, 初期変数shift=200)", label=f"{date}_func_table", position_float="centering", siunitx=True ) )# ICNVRT fig = px.scatter_3d(df_ICNVRT, x="process", y="na", z="#Call") fig.show()